5 Ways Your Brand Can (and Should) Use Big Data

Big data. You keep reading about it and hearing about it. You know you probably should be doing it but do you really understand why or where to start?

A few years back Professor of Psychology and Behavioural Economics, Dan Ariely summed up big data as being “like teenage sex: everyone talks about it but nobody really knows how to do it”.

Times have changed now. Lots of businesses are doing it, and doing it well, but other companies are still on the periphery of this trend, worried about the investment in both time and money required to get to grips with it.

If big data feels like an overwhelming concept to you, these five examples will show you how – on a practical level – it can be used by your brand. And if you think big data is prohibitively expensive, you’ll see how it can increase sales and deliver ROI.

Use Case 1: Using big data to optimise in-store product placement

A leading US brewer wanted to identify the best places to display its beers in the 500,000+ locations it was being stocked. They partnered with big data and predictive analytics provider IRI to obtain and analyse granular competitive data, by item and by store, on a weekly basis.

“While the client had already executed store-level strategies, additional granularity was required to account for the uniqueness of each store i.e. layout, shelf space, regional differences,” says IRI.

“IRI compiled over 100 internal and partner-provided data sets, spanning from point-of-sale and e-commerce information to digital measurement and gas price data, providing rich insight into aisle dynamics.”

Once the data had been cleaned and harmonised, IRI constructed brand hierarchies and assigned specific product attributes, distributed between specific segments. To analyse the data, a unique store-level assortment optimisation tool was created.

“The solution optimised the potential for each store across a variety of execution tactics. The tool was based on store-level shopper preferences (loyalty to 25 key beer attributes) as well as constraints such as floor and shelf space. It was also dynamic, allowing the client to make decisions quickly for each of its 500,000+ stores. The resulting assortment recommendations were also delivered via mobile to each route driver for execution.”

To test the product placements, the brewer set up a pilot scheme, implementing the recommendations in a number of stores and analysing the results versus a control group. It found that the stores using the recommended product positioning enjoyed incremental 2% portfolio growth per week, worth hundreds of millions of dollars in sales annually. The newly integrated data platform also dramatically improved new product forecasting through better understanding of store-level dynamics.

Use Case 2: Using big data to improve logistics at a live event

In the summer of 2018, Denmark’s Skanderborg Music Festival (Smukfest) teamed with IBM Denmark to capture and analyse data that would help it build a better festival experience.

A team of IBM volunteers spent eight days at the festival harnessing insights in real time from a Watson chatbot on food and beverage buying behavior, crowd safety, audience preferences and frequently asked questions.

With 60,000 attendees, huge levels of data were collected from around the event, from the use of rental vehicles to number of security teams to attendee location tracking.

“Smukfest uses wristbands with Near Field Communication chips to protect the digital user experience, allowing guests to securely pay for tickets, VIP festival access, food, drinks and accommodations amounting to 745,495 cashless transactions,” explains IBM.

IBM worked on four predetermined use cases based on available data:

  • Using transaction data from the purchase of food and beverages to help increase sales and decrease the time taken queuing
  • Analysis of attendee location data to help reduce overcrowding at stages and other potential safety hazards
  • Analysis of logistics patterns of vehicles used in the setup and cleanup operation to help identify areas for improved efficiencies
  • Development of a chatbot to provide festival goers with practical information

“The team followed every transaction from bars and restaurants, comparing categories with products over time and by revenue generated. This allowed the team to see how, for example, typically poorer tequila sales were tracking against the more popular gin and vodka drinks, which vendors were performing better than others, and even what time of day beer sold best.” says IBM.

Beyond optimising food and beverage sales Smukfest was able to map festival goers’ geo-tracking data into a timeline, detecting patterns of movement around the 148-acre festival site. This heatmap of guest movement was combined with geo-tracking data from the medical and security teams to made quick decisions on deployment to more crowded areas of the festival.

Use case 3: Using big data to guide business direction

German streaming service TV Spielfilm LIVE was facing a tough question about the direction of it app. It was torn between serving two audiences: should they they prioritise the large audience of free users, or the smaller audience of paying users?

For hard answers, TV Spielfilm LIVE turned to Finc3, a group of analytics consultants in Germany. Together they determined the metrics they would need to guide the direction of the product, both in the content it would deliver and in the users they would deliver it to.

“With TV Spielfilm LIVE we wanted to look at sign-ups, trials, feature adoption, and churn rates. And we needed to understand those metrics’ relationships to different types of content and channels,” says Bjoern Sjut, Founder and Managing Partner at Finc3.

Finc3 deployed Mixpanel to collect data from the multiple platforms customers use to stream TV, while user IDs were used to tie together all the user behaviors from across their devices to create a fully developed view of the user journey.

The numbers showed that the initial decision a user made to sign up for TV Spielfilm LIVE as either a free or premium customer had a huge impact on how they went on to use the product. Premium users were finding value from the product, watching for longer and coming back again and again. But free users weren’t, so they weren’t converting to premium.

“We decided to focus more of our time and resources on the premium product and its users,” says Carina Schwarzmueller, Business Intelligence Manager at TV Spielfilm LIVE. “Now we have just one product we can focus on but also, our users don’t have two products to decide between.”

The decision paid off. In the first month, the number of first-time visitors purchasing a paid subscription doubled. TV Spielfilm LIVE’s paid user base grew by 15% within two weeks. Now the streaming service is using data to dive even deeper into engagement and retention. By analysing key metrics like the number of streams, the duration of time watched, and the number of devices used, TV Spielfilm LIVE can identify early indicators of churn and proactively work to retain at-risk users.

Use case 4: Using big data to improve customer experience

Flying more than 30 million passengers a year, Scandinavian Airlines (SAS) generates copious amounts of data. The airline had started feeding that data into a CRM programme but wasn’t doing anything with it.

DXC Technology suggested taking customer support to the next level by connecting the data in the CRM to personalisation solutions. This enables the airline to meet the customer digitally at every touch point and every digital channel with tailored and dynamic messaging.

“We have a lot of insights about our customers, but the exciting thing is what we can do next,” says Christina von Euler, Head of Analytics & Development at SAS. “We’re just starting off with personalised communications, but we know there’s so much more we can do in terms of making sure they have the relevant offer in their channel of choice, looking into the future in terms of personalising the actual journey — how you get to the airport, do you want your meal on board, do you travel with a bag, all of that.”

“To attract Scandinavia’s frequent travellers, you need to offer a great customer experience,” adds Stefan Nilsson, SAS Vice President and CIO for corporate functions and analytics. “Analytics is a really important part of knowing the customer. We focus on analytics as an enabler to enhance and improve the customer experience and the operational excellence.”

Use case 5: Using big data to measure the success of promotions

A leading UK-based FMCG brand wanted to assess the impact of some newly designed loyalty initiatives, in the form of personalised product discounts accessible through their website.

“It was very difficult to isolate the impact of each initiative, as at the same time other factors such as baseline price fluctuations, competitor pricing and other promotions were also at play,” says commissioned agency Satori Analytics Agency.

Satori was asked to come up with a robust methodology of how to measure the impact of each initiative. It was important to the client that it could easily communicate the results to senior stakeholders, proving the value and ROI of the new initiatives.

Satori started by splitting the analysis into pre-and post-initiative periods and then built a custom clustering model. The model created homogeneous groups in terms of a customer’s buying behaviour i.e. how often they buy, what type of product, at what value. The agency then analysed the relative divergence in behaviour in those groups, by splitting each homogeneous group in two; those that used the initiative and those that didn’t.

“The results were astonishing,” says Satori. “We managed to quantify the impact of the initiative across thousands of customers and the sales uplift was proven to be in the region of tens of millions extra revenue per annum.

A final thought

Don’t dismiss big data as something that’s too complex or only for high tech businesses. As these use cases show, it can be applied to companies of all types to unearth highly valuable business intelligence.

You can discover how to sell more product, find ways to make efficiencies, better understand business priorities and measure the effectiveness of your marketing initiatives. But maybe even more importantly, big data gives you another window into customer behaviour – combine this with consumer insights and you can get to know your customers more intimately than ever before. To learn how Ask Attest.

Bel Booker

Senior Content Writer 

Bel has a background in newspaper and magazine journalism but loves to geek-out with Attest consumer data to write in-depth reports. Inherently nosy, she's endlessly excited to pose questions to Attest's audience of 125 million global consumers. She also likes cake.

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